Data integration projects have a similar failure rate to other technology projects. Although the statistics are not quite as tragic as for ERP or CRM implementation projects, data integration projects can also be risky.
When such a project fails, it is rarely purely due to technical issues. The actual data integration solution rarely makes a project fail.
This article will look into what makes or breaks data integration projects. It will start by analyzing the criteria that define the success of your projects. It will then point out which pitfalls one must avoid to avoid failure.
WHAT DOES DATA INTEGRATION SUCCESS MEAN?
Like with any other type of project, if you want to evaluate success, you need to have success criteria. For a data integration project, success criteria may vary according to the company’s industry, business processes or competitive environment.
Every data driven company entering a data integration project needs to define how they want to measure the success of their project. Generally, companies consider integrating systems when they are collecting considerable volumes of data from various data sources. They need to combine data and consolidate data to get the best business intelligence and make informed decisions.
Having a single, 360-degree view of their customer data can be one of their biggest challenges. Some have heterogeneous data stored in multiple data warehouses and in various data formats. Data audits can show horrific results. The time of big data can be complex to work with.
A data integration project can connect data sets from multiple sources and thereby provide a unified view of a company’s data. Success can then be measured by looking into system ROI, staff effectiveness, reduction in staff or better customer service leading to an increase in competitiveness.
4 MOST COMMON PITFALLS OF DATA INTEGRATION PROJECTS
Like any other technology projects, data integration projects can be complex. Securing a successful implementation and adoption needs to be a central consideration of the parties involved from day one. To do this, project leads and executive sponsors must be able to understand and avoid the most threatening data integration pitfalls.
# 1- Never ignore the limitations of some data integration solutions.
It has become more common for data integration vendors to provide pre-configured integration solutions. Or so they say. The reality is that these solutions are seldom ready to be used.
If you are looking for a plug-and-play integration solution to match your company’s specific needs and requirements, you might be disappointed.
Even the smallest changes to your systems to match your organization’s uniqueness could mean a lot of extra work to a so-called plug and play solution. Larger customizations could turn into a nightmare.
This does not mean that using pre-configured solutions is the wrong approach. Some of these solutions like RapidiOnline can easily be modified to match your needs. As long as you choose a flexible data integration platform, plan accordingly and set aside resources for adjustments, you should be fine.
# 2- Always remember to involve enough top executives.
IT is of course the center and leading part in any data integration project. However, it is important to involve other relevant parties across the company to secure their buy-in and support.
If you are integrating a CRM and ERP system, it makes sense to include representatives from your Sales and Marketing departments, as well as your Finance Department.
It would be a mistake to think that it is enough. Involving top level executives increases cooperation between stakeholders and data owners. This is a must to get the support and buy-in necessary to project success.
This is because a system integration project does more than “just” impact IT. It has an effect (hopefully a positive effect) much more broadly in your organization. Data integration means sharing data and automating processes. The most successful data integration projects usually involve a CIO or IT director, as well as a Managing Director, CEO or broad Board of Directors support.
# 3- Make your project an essential part of a long-term strategy.
Data integration projects don’t always stop with the integration of 2 isolated systems. Data integration can help optimizing a company’s business processes - all of them. When you start looking at the benefits of integrating two systems, you can often see that the integration could be extended to the rest of your systems.
Choosing to develop a custom integration between two of your systems can reveal a mistake if you decide later to integrate with the rest of your systems. It can be a good quick fix, but it rarely solves a company’s long term challenges.
Some ERP or CRM vendors have developed a one-off integration between systems for their customers. The problem with these integration solutions is that they are not developed to support additional integrations.
When you choose a data integration solution, you need to bear in mind that your data integration needs might evolve as your company evolves. A future proof data integration solution can be used when the integration constellation changes.
# 4- Don’t make data quality a second priority.
This is critical. Data management and data quality is the cornerstone of any system integration project. If you have poor data quality on one end, you will get poor data quality on the other end.
Data integration projects can only succeed if you have a company-wide focus on data quality throughout the system integration implementation project. This means having a focus on data cleaning already before the project starts. This also means having a focus on keeping the data quality high at the end of the project.
Good data quality is essential because it will secure the user-adoption required to make the project a success. Poor data quality will bring distrust among your users while high data quality will empower them to work more efficiently.
The best data integration projects always have a dedicated data quality champion.
A focus on these 4 points will allow you to get a good start with your project. Selecting the right data integration solution and vendor is important. Preparing your organization to the changes ahead is just as important and could make or break your project.
Learn more about the best way to secure the success of your data integration projects:
